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Record W4296009089 · doi:10.1364/ao.472141

Enhanced 2D finite element model and its application in laser cutting of carbon fiber reinforced plastic composites

2022· article· en· W4296009089 on OpenAlexaff
Yao Lu, PeiYing Gao, Jianan Xu, Yang Wang, Lijun Yang

Bibliographic record

VenueApplied Optics · 2022
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversity of Alberta
FundersNational Key Research and Development Program of China
KeywordsMaterials scienceComposite materialFinite element methodFibre-reinforced plasticCarbon fiber reinforced polymerHeat fluxStress (linguistics)Thermal conductionThermalLaserHeat transferOpticsComposite numberStructural engineeringMechanics

Abstract

fetched live from OpenAlex

A tailored 2D finite element model (FEM) is proposed to describe the temperature distribution and stress distribution by the UV nanosecond pulsed laser cutting of carbon fiber reinforced plastic (CFRP) composites. This model coupled thermodynamic and thermal stress and considers the heat conduction, thermal stress, and heat flux effects during the UV laser cutting of CFRP composites. In this study, the main mechanism of UV laser cutting of CFRP is elucidated, such as pressure gradient, plasma, and vaporization effects. The temperature field and stress field in a single pulse period are successfully simulated based on these theoretical models. We believe that this research will supply a theoretical reference for the UV laser cutting of CFRP composites and pave the way for applications in the aerospace industry in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.206
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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